Applying Human-Centered Design to Data Visualization

Jeff Knezovich over at On Think Tanks posted some great reflections from his recent trip to the Cartanga Data Festival, breaking down why data viz isn’t just a science but also an art. Data science alone, with its emphasis on statistics, code, and often technology, can’t develop the kind of simple yet artful visualizations that we find on feature blogs like Information is Beautiful or in reports to Ministries of Health that effectively advocate for new health facilities.

One of the highlights of his post was an insight into how he approaches data visualization training and design as a discipline that requires expertise in research, technology, design, and communication. Jeff unpacks (with some great resource links!) the importance of design from a visual and graphical sense, but I would argue that data viz design requires a certain level of understanding of the human experience of interacting with information. Who is your audience? How do they interact with information? What is their level of numeric literacy? How much do they care about the information you’re trying to communicate?

Applying these principles of design need not be onerous or feel intimidating for data visualization designers (though the facilitation guides and experts in this space can go deep in more involved program design). Next time you’re crafting something visual from a data set, think about these three things:

Who am I creating this for? Ask yourself this question repeatedly throughout the design process, not just at the very beginning. Understand both what they say they need from your analysis, but also their latent needs and expectations. If you’re working on a more complex project, like developing a dashboard, creating personas for your different users could be very helpful.

Prototype (sketch!), test, and iterate.Don’t be afraid to ask for feedback from your users or at the very least your colleagues throughout the design process. And don’t be afraid to make changes!

How will my audience use this product? How will your audience feel when they see your graph, chart, infographic, video, or dashboard? How will they interpret and use the data analysis you’ve presented? These considerations are key to ensuring your visualizations are used to promote evidence-led decision making.